Harnessing the “data deluge” is promoting new conversations between disciplines. Prof. Marciano and his collaborators have been pursuing research in a number of areas including: big cultural data, access to big heterogeneous data, records in the cloud, federated grid/cloud storage, visual interfaces to large collections, policy-based frameworks to automate content management, and distributed cyberinfrastructure to enable data sharing. But more importantly, innovative technical approaches require the convergence of creative insights across computer science, the social sciences, and the humanities. This talk touches on these topics and highlights a new collaboration with partners at Duke. Richard Marciano is a professor in the School of Information and Library Science at the University of North Carolina at Chapel Hill, Director of the Sustainable Archives and Leveraging Technologies (SALT) lab, and co-director of the Digital Innovation Lab (DIL). He leads development of "big data" projects funded by Mellon, NSF, NARA, NHPRC, IMLS, DHS, NIEHS, and UNC. Recent 2012 grants include a JISC Digging into Data award with UC Berkeley and the U. of Liverpool, called "Integrating Data Mining and Data Management Technologies for Scholarly Inquiry," a Mellon / UNC award called "Carolina Digital Humanities Initiative," which involves the translating of big data challenges into curricular opportunities, and an NSF award on big heterogeneous data integration. He holds a B.S. in Avionics and Electrical Engineering, and an M.S. and Ph.D. in Computer Science, and has worked as a postdoc in Computational Geography. He conducted interdisciplinary research at the San Diego Supercomputer at UC San Diego, working with teams of scholars in sciences, social sciences, and humanities.

1. "Socializing 'Big Data':
Collaborative Opportunities in
Computer Science, the Social Sciences, and the Humanities"
Richard Marciano
UNC Chapel Hill
richard_marciano@unc.edu
http://salt.unc.edu
http://digitalinnovation.unc.edu

2. Current research Areas
•records in the cloud,
•big cultural data,
•access to big heterogeneous data,
•federated grid/cloud storage,
•visual interfaces to large collections,
•policy-based frameworks to automate content management,
•distributed cyberinfrastructure to enable data sharing.

3. Records in the Cloud
Kickoff meeting on Feb. 5, 2013
•UBC iSchool, Faculty of Law, School of Bus.
•UW iSchool
•Mid-Sweden Info. Tech and Media,
Delegating to cloud providers the responsibility for security,
accessibility, disposition and preservation.

4. • Grids in Context
1998 •
• Larry Smarr
Computational Grids
• Ian Foster and Carl Kesselman
• Distributed Supercomputing Applications
• Paul Messina
• Realtime Widely Distributed Instrumentation
• William E. Johnston
• Data-Intensive Computing
• Reagan Moore, … Richard Marciano, …
• Teleimmersion
• Tom DeFanti and Rick Stevens
• Application-Specific Tools
• Henri Casanova, Jack Dongarra, …
• Compilers, Languages, and Libraries
• Ken Kennedy
• Object-Based Approaches
• Dennis Gannon, Andrew Grimshaw
• High-Performance Commodity Computing
• Geoffrey Fox, Wojtek Furmanski
• The Globus Toolkit
• Ian Foster, Carl Kesselman
• High-Performance Schedulers
• Francine Berman
• High-Throughput Resource Management
• Miron Livny, Rajesh Raman
• Instrumentation and Measurement
• Jeffrey Hollingsworth, Bart Miller
• Performance Analysis and Visualization
• Daniel Reed, Randy Ribler
• Security, Accounting, and Assurance
• Clifford Neuman
•
2003 Computing Platforms
Tony Hey: • Andrew Chien
“The Data Deluge: An e-Science Perspective” • Network Protocols
• P.M. Melliar-Smith, Louise Moser
• Network Quality of Service
• Roch Guerin, Henning Schultzrinne
• Operating Systems and Network Interfaces
• Peter Druschel, Larry Peterson
• Network Infrastructure
Collaborative Science
2004 •
• Jon Postel, Joe Touch
Testbeds: Bridges from Research to Infrastructure
• Charlie Catlett, John Toole

5. Big Data is a Big Deal
White House announcement:
http://www.whitehouse.gov/blog/2012/03/29/big-data-big-deal
Big Data Across the Federal Government:
http://www.whitehouse.gov/sites/default/files/microsites/ostp/big_data_fact_sheet_final_1.pdf
More then $200M in new commitments (NSF, HHS/NIH, DOE, DOD, DARPA, USGS)
Goal: “improve the ability to extract knowledge and insights from large and complex
collections of digital data”.
 DataNet
 Long-term preservation and access of data
 Software Infrastructure for Sustained Innovation (SI2)
 Digging Into Data Challenge (NSF/NEH/IMLS & JISC)
 Computational Humanities
 Cyber-Enabled Discovery and Innovation (CDI)
 Data enabled science and engineering
 Core Techniques and Technologies for Advancing Big
Data Science & Engineering (BIGDATA)
 Data Infrastructure Building Blocks (DIBBs)
 DataWay
 National Infrastructure for Heterogeneous Data

6. “Size Matters:
Big Data, New Vistas in the Humanities and Social Sciences”:
DataEdge, UC Berkeley May 31, 2012
Geoffrey Nunberg Panel:
“Something seems to happen, people feel, when you
get to that 13th zero, or 15th zero, or 18th zero, or 21st
zero, wherever it is, and bingo it’s the petabyte age, it’s
the age of big data.
It’s like combing your hair, you just comb, and comb,
and comb, and all of a sudden it’s like big hair.”
“The question is whether the advent of big data
changes the way we do social science and also what
role social scientists will play…”
12/31/2012 Forbes article by Edd Dumbill: “Big Data, Big Hype: Big Deal”
“Big data is an imprecise term. As such it’s a huge boon to marketers… not
everyone is pleased with the “bigger is better” argument. “Big data” really means
“smart use of data”.

7. Allistair Croll: “Big Data is our Generation’s civil rights issue, an we don’t know it.”
“Personalization” is another word for discrimination. We’re not discriminating if we tailor
things to you based on what we know about you — right? That’s just better service.
When bank managers tried to restrict loans to residents of
certain areas (known as redlining) Congress stepped in to
stop it (with the Fair Housing Act of 1968). They were able
to legislate against discrimination, making it illegal to change
loan policy based on someone’s race.
Home Owners’ Loan Corporation map showing redlining of “hazardous”
districts in 1936. see: DURHAM MAPS for T-RACES –project
Music selection and sharing with friends could allow to guess a person’s
racial background and deny a loan.
Publicly available last name information can
be used to generate racial boundary maps.
From the Mapping London project

8. Big Data = Big Collaborations

10. May 2007
Socializing CI:
Networking the Humanities,
Arts, and Social Sciences

11. TUCASI data-Infrastructure Project (TIP)
TUCASI data-Infrastructure Project (TIP)
Managing Digital Research Data in Federated Storage
Managing Digital Research Data in Federated Storage
Clouds
Clouds
• Project Lead: Richard Marciano (UNC/SALT)
• Project Manager: Amy Shoop (UNC ITS)
• Oversight Council
– CIOs -- Head Librarians
• Tracy Futhey -- Duke CIO Deborah Jakubs -- Duke Librarian
• Marc Hoit – NCSU CIO Susan Nutter – NCSU Librarian
• Larry Conrad – UNC CIO Sara Michalak – UNC Librarian
– RENCI
• Alan Blatecky -- RENCI Stan Ahalt -- RENCI
– DICE Center
• Reagan Moore – DICE
– SALT Lab
• Richard Marciano -- SALT

12. Focus Group Membership
University Teams
Focus
Duke Chapel Hill NC State
Groups
Suzanne Cadwell (ITS-Academic
Classroom Samantha Earp (CC Outreach & Engagement) Lou Harrison (DELTA)
lead) (OIT-Academic Charlie Greene (ITS-Teaching & Hal Meeks (OIT-Outreach,
Capture Services) Learning) Communications and Consulting)
Pam Sessoms (Lib-e-Reference)
Amy Brooks (OIT-Systems)
Klara Jelinkova (OIT- Reagan Moore (S lead) (DICE)
Shared Services & Leesa Brieger (RENCI-Data)
Infrastructure) Brent Caison (ITS-Storage) Steve Morris (Lib-Systems)
Storage David Kennedy (Lib-Info. Dave Pcolar (Lib-Systems) Eric Sills (OIT-Research Computing)
Sys. Support) Bill Schulz (Lib-Systems)
Molly Tamarkin (Lib- Lisa Stillwell (RENCI-Data)
Systems)
Jim Tuttle (Lib-Systems)
Future Data & Paolo Mangiafico (Provost- Ruth Marinshaw (ITS-Research Kristin Antelman (FD&P lead)
Computing)
Dig. Info. Strategy) (Lib)
Policy Tim Pyatt (Lib-Archives) Will Owen (Lib-Systems) Susan Nutter (Lib-Head Librarian)
Rich Szary (Lib-Special Collections)

13. 30 funded
57 total

14. “Public Scholarship”
Kathy Woodward, UW Simpson Center for the Humanities
UNC, Duke, Asheville collaboration
• University of North Carolina Asheville (UNCA): staff (provost, head librarian, head of
special collections, library staff, departments of computer science / history / political
science), centers (National Environmental Modeling and Analysis Center / Center for
Diversity Education), and students
• community-based development organizations (Green Opportunities Corps, Asheville
Design Center)
• neighborhood community group leaders and residents (Southside, Burton Street, East
End)
• city of Asheville officials (Housing Authority of the City of Asheville, Planning &
Development Department, West Asheville Public Library, Chamber of Commerce)
• county (head of Buncombe County Register of Deeds, Land-Of-Sky Regional Council)
• other groups including the North Carolina Humanities Council, Mountain Housing
Opportunities Inc.
• “Twilight of a Neighborhood: Asheville’s East End, 1970” project. This project
examined the process and aftermath of urban renewal and collected voices of residents,
after the 2007 transfer of records to UNC Asheville. We have secured support
and commitment from the community groups relevant to tackling this project.
• Asheville’s African-American Community Historical Bus Tour, June 19, 2012 (35
people)

18. UNCA & Asheville Partners:
• Dwight Mullen, UNCA Political Science
• Priscilla Ndiaye, chair of Asheville's Southside Advisory Commi

19. Big Heterogeneous Data (with Duke)
Mapping historical residential segregation in the
US
Researching the cyberinfrastructure implications of
supporting large scale content based indexing of highly
heterogeneous digital collections potentially embodying non-
uniform or sparse metadata architectures…
Intellectual Merit:
Demonstrating the creation of national collections through automation and citizen-
scientist crowdsourcing efforts is the focus of this task.
Broader Impacts:
This case-study will bring heterogeneous content from a variety of sources:
census, economic, historic, planning, insurance, financial, and scientific.
Outcomes:
Worfklows & Visual prototype

20. From Crowdsourcing to Citizen-led Sourcing
• Neighborhood community group leaders and residents (Southside, Burton Street, East End)
• University of North Carolina Asheville staff (provost, head of special collections, library staff, departments of
computer science / history / political science), centers (Renaissance Computing Institute / Center for Diversity
Education), and students
• Community-based development organizations (Green Opportunities Corps, Asheville Design Center)
• City of Asheville officials (Housing Authority of the City of Asheville, Register of Deeds, GIS, Planning &
Development Department, , West Asheville Public Library, Chamber of Commerce, Regional Council)
• Other groups including the North Carolina Humanities Council, Mountain Housing Opportunities Inc., Twilight
of a Neighborhood.

21. SALT
SALT
“We define the ‘discipline of data curation’ as the practice of collection,
annotation, conditioning , and preservation of data for both current and future
use”
– Helen Tibbo & Bryan H eidorn
Governance Policy
conditioning annotation
Content
collection
Infrastructure
preservation
current & future use
Evolution
Vectors – Annenberg Center for Communication SDSC: SALT